Postman is an API testing and debugging tool widely used in Linux systems. However, when running large API requests, frequently running automated tests, or interacting with complex backend services, performance bottlenecks can easily occur if not optimized, even affecting the accuracy of API response judgments. In Linux, Postman's operating efficiency depends not only on the software's settings but also on system-level optimizations. Here are some tips to make Postman run more smoothly and stably in Linux.

A crucial step in performance optimization is to properly allocate system memory. Running Postman in Linux relies on available RAM. If memory is insufficient, Postman's request processing speed will significantly decrease, especially when performing batch API tests or running collections. It's recommended to first run the command

free -h

to check the current system memory usage. If the memory usage is too high while Postman is running, you can reduce it by increasing physical memory or adjusting the swap space size. Execute

sudo swapon --show

to check swap space usage. A reasonable swap space can provide a buffer when memory is low, but it cannot replace high-performance physical memory.

Next, reduce unnecessary background processes. When launching Postman on a Linux system, if CPU resources are excessively occupied by other background processes, this can cause request processing delays. You can use

Top

or

Htop

to view real-time CPU usage and terminate unnecessary high-utilization processes to free up Postman for more computing resources. This method is particularly effective when performing high-concurrency API testing.

The third tip is to optimize Postman's cache and history data. Long-term use of Postman can accumulate a large amount of historical request records and cached data, which can slow down startup and request processing. Clear unused workspace history in Postman's settings and delete the Postman local cache directory in Linux, typically located at

~/.config/Postman

Deleting irrelevant data can significantly improve response speeds while also preventing the risk of accidental data leakage.

The fourth tip is to leverage command-line mode to run tests. In a Linux environment, if you need to batch execute API tests, using Postman's CLI tool, newman, can significantly reduce resource usage because it doesn't require the full GUI interface. For example:

newman run my_collection.json

This method is ideal for continuous integration (CI) environments. It's not only faster, but also works directly with tools like Jenkins and GitLab CI, improving automated testing efficiency.

The fifth tip is to adjust Linux file handle limits. During high-concurrency testing, Postman opens a large number of network connections and temporary files simultaneously. If the ulimit value is too low, request failures or timeouts can occur. You can view the current limit using

ulimit -n

and temporarily increase it using

ulimit -n 65535

 If you want a permanent effect, you can modify

/etc/security/limits.conf

to ensure that Postman is not limited by the system file handle limit under high concurrency.

The sixth optimization involves network adjustments. When running Postman on Linux to test APIs, network latency and packet loss can directly affect test speed. You can use

Ping

and

Mtr

to monitor the target server's network status. If latency is high, consider modifying the routing, using a proxy server, or adjusting the timeout settings in Postman to reduce latency. Additionally, enabling TCP Fast Open in Linux can also reduce handshake latency, with significant benefits in certain high-frequency request scenarios.

The final tip is to assign Postman a dedicated CPU core. On multi-core Linux systems, you can specify Postman to run on a specific core using the command

taskset -c 2 postman

to avoid competing for CPU resources with other high-utilization processes. This approach is particularly useful for performance testing that requires running Postman for extended periods, maintaining stable performance and avoiding fluctuations caused by system scheduling.

In short, optimizing Postman performance on Linux systems no longer relies solely on software configuration; it also requires comprehensive improvements through integration with Linux's underlying resource scheduling, network optimization, and operating mode adjustments. By optimizing memory management, reducing background processes, clearing caches, running tests using the CLI, increasing file handle limits, improving network configuration, and properly allocating CPU cores, Postman can ensure smooth and stable service even under high-load testing. This improves interface debugging efficiency while enabling cross-team collaboration and continuous focus, reducing wait times and improving the overall R&D and testing pace and quality.